Multi-Crop Sclerotinia sclerotiorum Apothecia Prediction Models for Irrigated Environments are Improved by On-Site Weather Monitoring and Supervised Machine Learning.
- DOI
- 10.1094/phyto-04-25-0126-r
- Published
- 2026 May
- Container
- Phytopathology
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1094/phyto-04-25-0126-r,
title = {Multi-Crop Sclerotinia sclerotiorum Apothecia Prediction Models for Irrigated Environments are Improved by On-Site Weather Monitoring and Supervised Machine Learning.},
author = {Check JC and Bales S and Dong Y and Smith DL and Webster RW and Willbur JF and Chilvers MI},
year = {2026},
journal = {Phytopathology},
doi = {10.1094/phyto-04-25-0126-r},
url = {https://doi.org/10.1094/phyto-04-25-0126-r}
}RIS
TY - JOUR TI - Multi-Crop Sclerotinia sclerotiorum Apothecia Prediction Models for Irrigated Environments are Improved by On-Site Weather Monitoring and Supervised Machine Learning. AU - Check JC AU - Bales S AU - Dong Y AU - Smith DL AU - Webster RW AU - Willbur JF AU - Chilvers MI PY - 2026 JO - Phytopathology DO - 10.1094/phyto-04-25-0126-r UR - https://doi.org/10.1094/phyto-04-25-0126-r ER -
APA
JC, C., S, B., Y, D., DL, S., RW, W., JF, W., & MI, C. (2026). Multi-Crop Sclerotinia sclerotiorum Apothecia Prediction Models for Irrigated Environments are Improved by On-Site Weather Monitoring and Supervised Machine Learning.. Phytopathology. https://doi.org/10.1094/phyto-04-25-0126-r
Source records
- pubmed · retrieved 2026-09-26T10:17:52.320Z